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Long-Time Memory in Drought via Detrended Fluctuation Analysis

  • Hasan TatliEmail author
  • H. Nüzhet Dalfes
Article

Abstract

The persistence of drought events largely determines the severity of socioeconomic and ecological impacts, unfortunately the performance of current weather forecasting models (WFM) to simulate such events is subject to great uncertainties. This study is investigating time-domain characteristics of drought persistence over Turkey by applying the detrended fluctuation analysis (DFA) method to the Palmer drought severity index (PDSI). The existence of long-range power-law correlation in PDSI fluctuations is demonstrated for time scales ranging from monthly to decadal. Understanding of such statistical patterns in PDSI values can definitely be a step forward in drought predictability. From a climatological point of view, it is found that the areas with high level DFA scaling exponent (generalized Hurst) indicate the areas of higher sensitivity to droughts and associated risks. Furthermore, the characteristics of the persistence of the PDSI in climate zones have also been examined by applying the Holdridge Life Zones (HLZ) classification. HLZ classification over Turkey leads to two climate-zones: cool-temperate and warm-temperate. In addition, when topography is taken in account, montane (cool-temperate) and lower-montane (warm-temperate) climate zones can be treated as two different zones. It has been observed that the predictable index (PI) of the PDSI derived from the DFA Hurst exponent is relatively high in the cool-temperate and montane climate zones compared to others. In fact, very different PI values were also obtained in a few HLZ climate classes within the same climate zone and with same vegetation index (i.e. steppe, dry-forest, warm-forest etc.).

Keywords

DFA Drought PDSI HLZ Long-memory Turkey 

Notes

Compliance with Ethical Standards

Conflict of Interest

The authors have no conflict of interest to publish this research.

References

  1. Alley WM (1984) The Palmer drought severity index: limitations and assumptions. J Clim Appl Meteorol 23(7):1100–1109CrossRefGoogle Scholar
  2. Bhardwaj R, Siddiqi AH, Mittal A (2012) Predictability index, fractal dimension and Hurst exponent estimation of carbon monoxide at different locations of Delhi. Indian J Industrial App Math 3(2):94–100Google Scholar
  3. Blender R, Fraedrich K (2003) Long time memory in global warming simulations. Geophys Res Lett 30(14).  https://doi.org/10.1029/2003GL017666
  4. Byun HR, Wilhite DA (1999) Objective quantification of drought severity and duration. J Clim 12(9):2747–2756CrossRefGoogle Scholar
  5. Carbone A, Castelli G, Stanley HE (2004) Analysis of clusters formed by the moving average of a long-range correlated time series. Phys Rev E 69(2):026105CrossRefGoogle Scholar
  6. Cohen J, Saito K, Entekhabi D (2001) The role of the Siberian high in northern hemisphere climate variability. Geophys Res Lett 28(2):299–302CrossRefGoogle Scholar
  7. Gibbs WJ, Maher JV (1967) Rainfall Deciles as drought indicators. Bureau of Meteorology: Melbourne, Australia, p 29Google Scholar
  8. Gu GF, Zhou WX (2006) Detrended fluctuation analysis for fractals and multifractals in higher dimensions. Phys Rev E 74:061104CrossRefGoogle Scholar
  9. Guttman NB (1998) Comparing the palmer drought index and the standardized precipitation index 1. J Am Water Resour As 34(1):113–121CrossRefGoogle Scholar
  10. Heim RR (2000) Drought indices: a review. Drought: a global assessment:159–167Google Scholar
  11. Heim RR (2002) A review of twentieth-century drought indices used in the United States. B Am Meteorol Soc 83(8):1149–1165CrossRefGoogle Scholar
  12. Holdridge L (1967) Life zone ecology, Tropical Science Center. San Jose´, Costa RicaGoogle Scholar
  13. Hou W, Feng G, Yan P, Li S (2018) Multifractal analysis of the drought area in seven large regions of China from 1961 to 2012. Meteor Atm Phys 130:459–471CrossRefGoogle Scholar
  14. Hu D, Shu H, Hu H, Xu J (2017) Spatiotemporal regression Kriging to predict precipitation using time-series MODIS data. Cluster Comput 20(1):347–357CrossRefGoogle Scholar
  15. Intergovernmental Panel on Climate Change (IPCC) (2013) Climate change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by T. F. Stocker et al., Cambridge University Press, Cambridge, U. K.Google Scholar
  16. Ivanova K, Ausloos M (1999) Application of the detrended fluctuation analysis (DFA) method for describing cloud breaking. Physica A: Statistical Mechanics and its Applications 274:349–354CrossRefGoogle Scholar
  17. Kantelhardt JW, Zschiegner SA, Koscielny-Bunde E, Havlin S, Bunde A, Stanley HE (2002) Multifractal detrended fluctuation analysis of nonstationary time series. Physica A 316:87–114CrossRefGoogle Scholar
  18. Khalyani AH, Gould WA, Harmsen E, Terando A, Quinones M, Collazo JA (2016) Climate change implications for tropical islands: interpolating and interpreting statistically downscaled GCM projections for management and planning. J App Meteor Climatol 55(2):265–282CrossRefGoogle Scholar
  19. Kogan FN (1997) Global drought watch from space. B Am Meteorol Soc 78(4):621–636CrossRefGoogle Scholar
  20. Liu D, Luo M, Fu Q, Zhang Y, Imran KM, Zhao D, Abrar FM (2016) Precipitation complexity measurement using multifractal spectra empirical mode decomposition Detrended fluctuation analysis. Water Resour Manag 30:505–522CrossRefGoogle Scholar
  21. Marcos-Garcia P, Lopez-Nicolas A, Pulido-Velazquez M (2017) Combined use of relative drought indices to analyze climate change impact on meteorological and hydrological droughts in a Mediterranean basin. J Hydrol 554:292–305CrossRefGoogle Scholar
  22. McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. In Proceedings of the 8th Conference on Applied Climatology (Vol. 17, no. 22, pp. 179-183). Boston, MA: American Meteorological SocietyGoogle Scholar
  23. Mishra AK, Singh VP (2010) A review of drought concepts. J Hydrol 391(1–2):202–216CrossRefGoogle Scholar
  24. Mukherjee S, Mishra A, Trenberth KE (2018) Climate change and drought: a perspective on drought indices. Current Climate Change Reports:1–19Google Scholar
  25. Palmer WC (1965) Meteorological drought. Research paper no. 45. Office of Climatology. U.S. weather bureau, WashingtonGoogle Scholar
  26. Peng CK, Buldyrev SV, Havlin S, Simons M, Stanley HE, Goldberger AL (1994) Mosaic organization of DNA nucleotides. Phys Rev E 49(2):1685CrossRefGoogle Scholar
  27. Podobnik B, Horvatic D, Petersen AM, Stanley HE (2009) Cross-correlations between volume change and price change. P Natl A Sci India A 106(52):22079–22084CrossRefGoogle Scholar
  28. Rego CRC, Frota HO, Gusmão MS (2013) Multifractality of Brazilian rivers. J Hydrol 495:208–215CrossRefGoogle Scholar
  29. Rossi G, Benedini M, Tsakiris G, Giakoumakis S (1992) On regional drought estimation and analysis. Water Resour Manag 6:249–277CrossRefGoogle Scholar
  30. Shafer BA, Dezman LE (1982) Development of a surface water supply index (SWSI) to assess the severity of drought conditions in snowpack runoff areas. In proceedings of the Western snow conference, Colorado State University, Fort Collins, CO, USA, 19–23 April 1982; pp. 164–175Google Scholar
  31. Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35(2):1–7CrossRefGoogle Scholar
  32. Surendran U, Kumar V, Ramasubramoniam S, Raja P (2017) Development of drought indices for semi-arid region using drought indices calculator (DrinC)–a case study from Madurai District, a semi-arid region in India. Water Resour Manag 31:3593–3605CrossRefGoogle Scholar
  33. Szelepcsényi Z, Breuer H, Kis A, Pongrácz R, Sümegi P (2018) Assessment of projected climate change in the Carpathian region using the Holdridge life zone system. Theor Appl Climatol 131(1–2):593–610CrossRefGoogle Scholar
  34. Tatli H, Dalfes HN (2016) Defining Holdridge's life zones over Turkey. Int J Climatol 36(11):3864–3872CrossRefGoogle Scholar
  35. Tatli H, Türkeş M (2011) Empirical orthogonal function analysis of the Palmer drought indices. Agric For Meteorol 151(7):981–991CrossRefGoogle Scholar
  36. Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38(1):55–94CrossRefGoogle Scholar
  37. Tsakiris G, Pangalou D, Vangelis H (2007) Regional drought assessment based on the reconnaissance drought index (RDI). Water Resour Manag 21:821–833CrossRefGoogle Scholar
  38. Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23(7):1696–1718CrossRefGoogle Scholar
  39. Voss RF (1991) Random fractals: characterization and measurement. In Scaling Phenomena In Disordered Systems (pp. 1-11). Springer, Boston, MAGoogle Scholar
  40. Webb R, Rosenzweig CE, Levine ER (2000) Global soil texture and derived water-holding capacities. ORNL DAAC., data set. Available from oak Ridge National Laboratory distributed active archive center, oak ridge, Tennessee, USA. http://www.daac.ornl.gov (accessed 1 May 2017)
  41. Wilhite DA (2000) Drought as a natural hazard: concepts and definitions. In Drought: A Global Assessment Wilhite; Routledge: London, UK 1:3–18Google Scholar
  42. Wilhite DA, Glantz MH (1985) Understanding: the drought phenomenon: the role of definitions. Water Int 10(3):111–120CrossRefGoogle Scholar
  43. Wilhite DA, Svoboda MD, Hayes MJ (2007) Understanding the complex impacts of drought: a key to enhancing drought mitigation and preparedness. Water Resour Manag 21:763–774CrossRefGoogle Scholar
  44. Yuan X, Ji B, Tian H, Huang Y (2014) Multiscaling analysis of monthly runoff series using improved MF-DFA approach. Water Resour Manag 28(12):3891–3903CrossRefGoogle Scholar
  45. Zargar A, Sadiq R, Naser B, Khan FI (2011) A review of drought indices. Environ Rev 19(NA):333–349CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2020

Authors and Affiliations

  1. 1.Department of GeographyFaculty of Sciences and Arts, Çanakkale Onsekiz Mart UniversityÇanakkaleTurkey
  2. 2.Eurasia Institute of Earth SciencesIstanbul Technical UniversityIstanbulTurkey

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